Understanding the Role of Social Media in the Assessment of Retailer-Hosted Consumer Reviews

Agile methods incorporate many techniques that support coordination in co-located software development teams. However, these benefits do not necessarily transfer to a distributed context. Even though research on coordination in distributed agile software development is growing, there is limited rigorous research on its application in context. Further the extant literature is fragmented, with little cohesive building of cumulative knowledge on coordination in distributed agile software development. This study investigates the scientific evidence between 2006 and 2016 by conducting a systematic review of the literature on coordination in distributed agile software development. The search strategy resulted in 178 studies, of which 50 were identified as primary studies relevant to this research. The studies were classified using three high-level categories: (i) theoretical foundation and application, (ii) tools and techniques, and (iii) challenges. This study provides a structured overview of the current state of knowledge on coordination in distributed agile development, and identifies opportunities for future research

The Longer the Better? The Interplay Between Review Length and Line of Argumentation in Online Consumer Reviews

Review helpfulness serves as focal point in understanding customers’ purchase decision-making process on online retailer platforms. An overwhelming majority of previous works find longer reviews to be more helpful than short reviews. In this paper, we propose that longer reviews should not be assumed to be uniformly more helpful; instead, we argue that the effect depends on the line of argumentation in the review text. To test this idea, we use a large dataset of Amazon customer reviews in combination with a state-of-the-art approach from natural language processing that allows us to study the line of argumentation at sentence level. Our empirical analysis suggests that the frequency of argumentation changes moderates the effect of review length on helpfulness. Altogether, we disprove the prevailing narrative that longer reviews are uniformly perceived as more helpful. Retailer platforms can utilize our results to optimize their customer feedback system and to feature more useful reviews

Sentence-Level Sentiment Analysis of Financial News Using Distributed Text Representations and Multi-Instance Learning

Researchers and financial professionals require robust computerized tools that allow users to rapidly operationalize and assess the semantic textual content in financial news. However, existing methods commonly work at the document-level while deeper insights into the actual structure and the sentiment of individual sentences remain blurred. As a result, investors are required to apply the utmost attention and detailed, domain-specific knowledge in order to assess the information on a fine-grained basis. To facilitate this manual process, this paper proposes the use of distributed text representations and multi-instance learning to transfer information from the document-level to the sentence-level. Compared to alternative approaches, this method features superior predictive performance while preserving context and interpretability. Our analysis of a manually-labeled dataset yields a predictive accuracy of up to 69.90 %, exceeding the performance of alternative approaches by at least 3.80 percentage points. Accordingly, this study not only benefits investors with regard to their financial decision-making, but also helps companies to communicate their messages as intended

Information Overload in Processing Consumer Reviews: The Role of Argumentation Changes

Information overload theory suggests that consumers can only processa certain amount and complexity of information. In this study, we analyze whetherinformation overload can also occur while processing individual product reviewswith a high rate of argumentation changes. An argumentation change denotes achange from positive to negative arguments, and vice versa.We propose a NeuroISexperiment in which participants are presented a given set of product reviews witha low or high rate of argumentation changes. The participants are asked about theirperceived helpfulness of the product review, their purchase intention for the product,and self-reported information overload. During the experiment, we measurecognitive activity based on electroencephalogram (EEG) and eye-tracking. Weexpect that a higher rate of argumentation changes is linked to greater cognitive activity,and, in particular, lower perceived review helpfulness and purchase intention

Natural Language Processing for Medical Texts – A Taxonomy to Inform Integration Decisions into Clinical Practice

Electronic health records (EHR) have significantly amplified the volume of information accessible in the healthcare sector. Nevertheless, this information load also translates into elevated workloads for clinicians engaged in extracting and generating patient information. Natural Language Process (NLP) aims to overcome this problem by automatically extracting and structuring relevant information from medical texts. While other methods related to artificial intelligence have been implemented successfully in healthcare (e.g., computer vision in radiology), NLP still lacks commercial success in this domain. The lack of a structured overview of NLP systems is exacerbating the problem, especially with the emergence of new technologies like generative pre-trained transformers. Against this background, this paper presents a taxonomy to inform integration decisions of NLP systems into healthcare IT landscapes. We contribute to a better understanding of how NLP systems can be integrated into daily clinical contexts. In total, we reviewed 29 papers and 36 commercial NLP products

Smart Cities and Digitized Urban Management

By 2050, two-thirds of the world’s population is expected to reside in cities and urban agglomerations (UN Department of Economic and Social Affairs 2014). Cities have always showcased the best and the worst aspects of humanity – gleaming skyscrapers, art, and inventiveness on the one hand; slums, crime, and abject poverty on the other. Such challenges, which cities already face, will be further amplified by increasing urbanization, and it will be coastal cities in particular that bear the brunt of the global threat of climate change. Not without reason is the quest for “Sustainable Cities and Communities” one of the UN’s explicit sustainable development goals (United Nations 2015)

Physician empathy: Definition, outcome-relevance and its measurement in patient care and medical education

Objective: The present study gives a brief introduction int